A Three-Dimensional Partial Weight Tensor Model for Teaching Recommendation

被引：0
|
作者：
Yao D.-H. [1 ,2 ]
Li S.-J. [2 ]
Hu Y.-H. [2 ,3 ]
机构：
[1] College of Computer Science & Engineering, Huaihua University, Huaihua, 418000, Hunan
[2] School of Computer, Wuhan University, Wuhan
[3] The Fourth Department of Air Force Early Warning Academy, Wuhan
来源：
| 2017年 / Univ. of Electronic Science and Technology of China卷 / 46期
关键词：
Data reduction; Teaching recommendation; Tensor decomposition; Three-dimensional partial weighted tensor;
D O I：
10.3969/j.issn.1001-0548.2017.05.018
中图分类号：
学科分类号：
摘要：
To address the problem that the teaching arrangements are not on the basis of recommendation in current school, a series of formalized methods are used to specify teachers' specialty foundation, course difficulty, and teaching evaluation first. Then, a kind of weighted function is defined to calculate the comprehensive partial weight for each group of teachers' professional foundation, course difficulty, and teaching evaluation. Next, the three-dimensional tensor model with partial weight is built on the 4-tuples relation of teacher-course- evaluation-weight and the comprehensive weight is endowed to the tensor elements. Finally, on the basis of above,a new kind of decomposition algorithm based on Tucker Decomposition is designed to obtain the approximate tensor of dimensionality reduction with the higher-order singular value decomposition (HOSVD), achieving the Top-N recommendation of teaching arrangements. Experiment results show that our proposed method can realize precise teaching arrangements recommendations when the iterative threshold value reaches a reasonable value, which can be used as a new intelligent recommendation method applied to the teaching arrangements in all kinds of schools. © 2017, Editorial Board of Journal of the University of Electronic Science and Technology of China. All right reserved.
引用
收藏
页码：747 / 754
页数：7
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